Learner Uptake of Teacher Electronic Feedback in ESL

Learner Uptake of Teacher Electronic Feedback in ESL Composition

Estela Ene Department of English

Assistant Professor of English, Director of the English for Academic Purposes Program Indiana University-Purdue University Indianapolis

CA 341D, 425 University Blvd, Indianapolis, IN 46202 [email protected]

Abstract The research on electronic feedback in second language writing is scarce, despite the increasingly frequent use of computers in ESL writing classrooms. The current study's purpose is to determine (1) what types of electronic written feedback ESL learners receive on writing that has been submitted and returned electronically, and (2) the relationship between teacher feedback and uptake. Twelve ESL students and three teachers participated in this longitudinal study. Multiple drafts of two essays from two semesters of college-level first-year composition were analyzed. The findings show that most of the teachers' electronic feedback consisted of marginal comments that were, for the most part, directive, explicit, principled, systematic, and needs-based – much like handwritten feedback. Importantly, electronic feedback was successful at eliciting appropriate revisions of grammatical structures or surface-level features, but also content and organization. This suggests that electronic feedback can be effective and therefore should not be avoided. Keywords: Electronic; Written corrective teacher feedback; Uptake; ESL composition; L2 writing

This is the author’s manuscript of the article published in final edited form as: Ene, E., & Upton, T. (2014). Learner uptake of teacher electronic feedback in ESL composition. System, 46, 80-95. Available from: http://dx.doi.org/10.1016/j.system.2014.07.011

http://dx.doi.org/10.1016/j.system.2014.07.011

mailto:[email protected]

Introduction

The efficacy of feedback on language development has been an important and

controversial issue in second language acquisition (SLA) in general and, since the 1990s, in

second language writing (SLW) studies in particular. The idea that feedback – oral or written –

supports SLA derives from several theories. First, corrective feedback is hypothesized to aid in

language acquisition because it creates opportunities for interaction and meaning negotiation,

and provides a learner with the input needed for acquiring language while also making the input

more comprehensible for the learner – as posited by the widely accepted Interaction Hypothesis

(Long, 1996). In addition, the value of feedback is connected to Schmidt’s Noticing Hypothesis

(1990, 1995, 2001), which holds that “SLA is largely driven by what learners pay attention to

and notice in target language input and what they understand the importance or significance of

noticed input to be” (Schmidt, 2001, p. 3-4). Researchers of SLW (e.g., Qi & Lapkin, 2001;

Swain, 1998) have also argued that writing provides opportunities for learners to focus on input

and notice the gap between their interlanguage and the target language (Gass, 1997). The value

of feedback in language development is also supported by Swain’s (1985, 1995) Output

Hypothesis, which claims that pushing students to produce challenging output raises a learner’s

awareness of linguistic input and gaps. Corrective feedback is hypothesized to encourage

students to produce language above their independent abilities, facilitating their progress towards

the target language.

Indeed, some studies suggest that student writers responding to feedback display

outcomes that match the predictions of SLA theories. For example, Sheen (2007, 2010) and

Ferris and Roberts (2001) argue that students’ command of linguistic forms improves when they

attend to feedback due to having their attention drawn to input-output gaps. In addition, studies



that analyze uptake and revisions – Chandler (2003), Ferris (2006), Heift (2004), Storch and

Wigglesworth (2010), and Santos, López-Serrano and Manchón (2010) – describe the presence

of corrections and revisions as support for the Output Hypothesis. However, it has been noted

that research design inconsistencies have made it difficult to generalize findings from studies on

written feedback in SLW (Ellis, 2009; Ferris, 2004; Guénette, 2007) and fueled prominent

arguments between those who see feedback as largely useless (e.g., Truscott, 1996, 1999, 2004)

and those who do not (e.g., Bruton, 2010; Ferris, 1999, 2004). For each study that illustrates the

effectiveness of feedback, reviewers find that there is a research design flaw, another study with

contradicting findings, or no other research to back up conclusions (for detailed reviews, see

Ellis, 2009; Ferris, 2011; Bitchener & Ferris, 2012). The currently accepted hypothesis is that

“there is some role for written CF [corrective feedback] in L2 instruction, although the nature

and extent of this role remains in dispute” (Ferris, 2010, p.183). With the growing use of

technology-enhanced instruction, two important questions warrant further study with regard to

SLW instruction: Is electronic feedback useful to learners? If so, which types of electronic

feedback do learners attend to and lead to improved accuracy, long-term retention of linguistic

forms, and overall improved language use?

1. Literature review

To provide context for the current study, this section first reviews the most important

concepts and findings from the research on the effectiveness of written feedback in SLW. An

overview of the few studies that have been done on feedback in online environments is then

provided, including findings on synchronous and asynchronous peer and teacher feedback.

1.1. Feedback



The focus of earlier studies on feedback in SLW was primarily on the effects of direct or

indirect feedback on grammatical accuracy (Chandler, 2003; Ferris & Roberts, 2001; Lalande,

1982; Robb et al., 1986) and on the effects of feedback on form and/or content (Ashwell, 2000;

Fathman & Whalley, 1990; Fazio, 2001; Semke, 1984), reflecting that fact that SLW studies

have drawn heavily on studies of oral feedback in exploring types of written feedback. For

example, SLW studies typically describe feedback as direct or indirect, a key feature of oral

corrective feedback. In his review, Ellis (2009) notes that direct corrective written feedback can

consist of “crossing out an unnecessary word, phrase, or morpheme, inserting a missing word or

morpheme, and writing the correct form above or near to the erroneous form” (p.99). Codes,

metalinguistic explanations and examples have also been identified as types of direct feedback

by Bitchener and Knoch (2009, 2010), although Storch and Wigglesworth (2010) and Guénette

(2007) argue that codes better represent indirect feedback. As described by Ellis (2009, p. 100),

indirect feedback “involves indicating that the student has made an error without actually

correcting it,” including underlining or highlighting the errors, or placing a mark in the margin of

the text containing an error.

In addition, some studies on written feedback in SLW development have explored the

distinction between explicit and implicit feedback, also a major focus of interest in the research

on oral feedback. Ellis (2009) and Sheen (2007) argue that the implicit-explicit dimension does

not apply to written feedback, which they believe – by virtue of being written – can only be

explicit; nevertheless, studies which consider this distinction as a feature of written feedback

have been done. Li (2010) in a comprehensive meta-analysis of feedback in SLW studies insists

on the importance of the implicit-explicit continuum. Based on a review of feedback studies in

SLW and the original typology by Lyster and Ranta (1997), Li notes:



implicit feedback included recasts, negotiation (clarification requests, elicitation, and repetition), and any type of feedback that was not intended to overtly draw the learner's attention to his/her erroneous production; explicit feedback included metalinguistic feedback, explicit correction, and any feedback type that overtly indicated that the learner's L2 output was not acceptable… The implicit versus explicit dichotomy is necessary because it has been argued that explicit feedback is superior to implicit feedback in SLA because the former is more salient. (p. 11)

Some SLW researchers have been interested in capturing nuances of teacher feedback

beyond directness and explicitness. For example, Ferris et al. (1997) sorted comments based on

intent or purpose. Their classification included: directives such as asking for information, making

a suggestion or request, or giving information; grammar/mechanics comments; and positive

comments.

As pointed out in comprehensive reviews by Ellis (2009) and Bitchener & Ferris (2012),

one conclusion that can be extracted from studies on written corrective feedback is that when

feedback is present, learners’ accuracy and fluency seem to improve, even if only for the

duration of the study, when compared with control groups who receive no feedback at all.

However, the results are mixed regarding which specific types and combinations of feedback are

beneficial and long-lasting. Additionally, a limitation of most studies on feedback in SLW is that

they artificially isolate either feedback that focuses on certain forms (e.g., nouns or sentence

structure; see for example Bitchener, 2008; Ellis et al., 2008; Ferris & Roberts, 2001; also Ferris,

2010; Xu, 2009) or selected types of feedback (e.g., coding, circling, or error description; see for

example Chandler (2003) and Ferris & Roberts (2001)). This leaves us without a comprehensive

understanding of the effectiveness of a variety of feedback techniques considered together, the

way they are typically used in real classrooms (Ellis, 2009; Hyland & Hyland, 2006).

1.2. Electronic Feedback



The use of computers and other technology has become common in educational contexts,

and is often preferred by students and teachers of SLW (Hyland, 2010). It has become common

for teachers of writing, particularly in university contexts, to require students to submit their

papers electronically through classroom management programs like Blackboard, and for teachers

to provide feedback on student papers electronically in chats, forums, or via word-processing

software. Studies on feedback in SLW and computer-assisted language learning (CALL) use the

term electronic feedback, or e-feedback, to refer to computer-facilitated feedback produced by

either the teacher or student peers with the help of a computer and delivered electronically to the

student. Computer-facilitated feedback such as comments, track changes, or feedback provided

in synchronous or asynchronous computer mediated communication (CMC) is distinct from

computer-generated feedback – or automated writing evaluation (AWE), which provides

automated algorithm-derived feedback drawn from an existing database of comments or

corrections (Heift, 2001, 2004, 2010; Warden & Chen, 1995; Ware, 2011). While computer-

generated feedback shares some similarities with computer-facilitated feedback, the focus of this

study is on the latter.

To date, studies of human e-feedback have focused primarily on CALL as a means to

enhance SLW by facilitating learning as a social activity through computer-mediated interaction

with peers (Lantolf, 1994; van Lier, 2000). Liu and Sadler (2003), Schultz (2000), and Tuzi

(2005) have observed that on-line, written feedback from peers, through chat rooms or classroom

websites, is more beneficial than oral feedback, even though students tend to prefer to engage

face-to-face. However, Ware and O’Dowd (2008) noted that peers who engaged in written forum

discussions offered feedback on form only when required, and incorporated little of the language



modeled by their peers in their own written posts. This observation led to their conclusion that

teachers may still be the best ones to offer useful feedback.

The current body of research on e-feedback from teachers is limited. In particular, to our

knowledge, there are no studies that describe comprehensively the use and the impact on student

writing of e-feedback by skilled teachers in non-experimental, SLW classrooms. There are a few

studies that analyze e-feedback strategies used by tutors or teachers-in-training in written

interactions with language learners in discussion forums. Zourou (2011) found that tutors’

feedback focused on both form and meaning, but the proportional distribution of these feedback

types is not provided. Additionally, the effectiveness of the feedback as illustrated by learner

uptake was not analyzed. Using a similar tellecollaborative setting with English language

learners from Taiwan and ESL writing tutors/teachers in-training from the U.S., Martin-Beltran

and Chen (2013) conducted a case study of one tutor’s feedback to two graduate ESL students in

an online forum discussion. Their analysis of 47 comments revealed that the tutor used a variety

of speech acts, leading the authors to conclude that asynchronous comments can be as interactive

as synchronous ones; 92% of the comments resulted in uptake. The feedback formulated as

interrogatives and hedges led to most revisions, and the learners reported increased awareness of

language and revisions. Samburskiy and Quah (2014) studied the online written interaction of

novice online tutors with Belarusian college-level English learners and found that most of the

feedback provided by the tutors focused on meaning rather than form. Despite this finding, the

authors focused their analysis on the form-focused feedback and determined that recasts and

textual enhancements were used most frequently, while explicit feedback was combined with

metalinguistic information. Lexical errors were more frequently targeted than grammatical

errors. The study revealed inconsistent learner responses and no statistically significant uptake of



the tutors’ e-feedback. Explicit and metalinguistic feedback elicited more responses than implicit

feedback, as noted by Bitchener et al. (2005), Bitchener and Koch (2010), and Heift (2004). In a

study of synchronous feedback offered by native-speaking peers to English language learners

from Sweden via a chat, Sauro (2009) focused on recasts and metalinguistic feedback about the

use of the zero article with abstract nouns. The study found an increase in accuracy for the

metalinguistic feedback, but the increase was not significant.

In sum, the research conducted so far on teacher electronic feedback is scarce, even

though most scholars deem teacher feedback as more appropriate and impactful than the e-

feedback of peers. In addition, like many experimental studies on written corrective feedback,

most CALL studies of e-feedback either pick and choose the kind of feedback that is analyzed or

neglect uptake altogether. Importantly, more attention has been focused on written responses

from discussion forums rather than essay-writing per se, and thus have diminished relevance for

teachers who want to learn how to comment directly on essay drafts.

2. Overview of the study

The present study is motivated by gaps in our understanding of written feedback in

general, and teacher electronic feedback in particular. First of all, due to their selective focus and

short duration, SLA-oriented studies of feedback have not enhanced our understanding of

feedback as a complex combination of a variety of types of comments and corrections, and so do

not reflect how feedback is actually offered by teachers outside of experimentally designed

studies (Ferris, 2010). Since the advent of the process approach in writing instruction and its

adoption as a preferred approach to teaching writing in the U.S. (Hyland, 2003), teacher

feedback in ESL contexts, particularly since the 1990s, has focused not only on linguistic forms,

but also on content, organization, style, process steps, and other aspects of written discourse.



(For a review of pedagogical approaches to SLW, see Hyland, 1996, 2010.) Teachers often offer

feedback via comments of varying lengths (from a single mark to multiple sentences), in a

variety of locations (such as in the margins and at the end of a paper), using both a variety of

types of propositions or speech acts (questions, commands, suggestions) as well as specialized

markings and codes – all in the same paper (Baker & Bricker, 2010).

Second, more longitudinal studies of feedback in SLW are needed. As noted by Ferris

(2010), recent “compositionist” studies of feedback in SLW have sought to explore whether

written feedback helps improve the overall texts and writing skills of student writers in non-

experimental, classroom contexts (Chandler, 2003; Ferris, 1995, 2006; Foin & Lange, 2007).

However, only a few of these studies would be considered “longitudinal” in any sense of the

term, and the study of feedback beyond one course or semester is rare (Ellis, 2009; Ferris, 2010).

Third, the growing prevalence of electronic feedback increases the importance of

understanding how effective feedback in a CALL environment is on SLW development. The

features of electronically provided feedback are largely assumed to be the same as those of

handwritten feedback, but a focused analysis has not been performed, in particular one involving

teacher e-feedback on essay drafts. As Ware and Warschauer (2006) note, “As teachers turn to

research-based evidence for answers about how best to use technology for providing feedback,

they deserve a critically informed, empirically based inquiry that makes explicit how electronic

feedback was used, and the criteria that were applied to evaluate its effectiveness” (p. 105-106).

The purpose of this study is to look more closely at both the kinds of electronic feedback

students receive and how they respond (if they do) to that feedback in writing courses where

papers are submitted and evaluated in an electronic environment, and to compare the results with

what we know about the influence of handwritten feedback on SLW development. The study



addresses the following questions: (1) What kind of teacher feedback do ESL learners in a

university context receive on writing assignments that have been submitted and returned

electronically? (2) What is the relationship between teacher electronic feedback (TEF) and

student uptake?

3. Method

To answer the above research questions, the study takes a comprehensive, longitudinal

look at naturally occurring, asynchronous, text-based teacher e-feedback (TEF) and the resulting

student uptake in college-level ESL composition courses. The study is an observational,

correlational cohort study that observes a group of participants, without manipulating the

variables, over a period of time in multiple waves of data collection (time-series). Ortega and

Iberri-Shea (2005) note that longitudinal SLA studies sometimes span shorter periods of time

(meaning, not years or decades) due to institutional constraints, such as the length of a program.

In this study, the SLW course sequence at the participating institution only lasts two semesters.

Consequently, this study falls in the category of “programmatic longitudinal studies” (Ortega &

Iberri-Shea, 2005, p.5). The sections below provide information about the participants, materials,

tools, and procedures used.

3.1. Participants

The participants were 12 non-native English speakers who had matriculated into

undergraduate engineering programs in a Midwestern U.S. university, and who had placed

through an entrance exam into credit-bearing courses in the English for Academic Purposes

(EAP) Program (housed in the department of English) that they took concurrently with other

first-year courses. Six students were from China and six were from Saudi Arabia. One Chinese

and three Saudi students had been enrolled in a local intensive English program for at least a



semester prior to the EAP Program, and four Saudi students had taken a basic integrated skills

EAP course before starting their writing courses. None of the participants had experience taking

online language courses; all had emailed writing assignments before, but had usually received

handwritten feedback on them. All of the participants were in their early twenties, and all were

males. The participants represented the two primary cultural groups in the program and met the

conditions necessary for the study: (a) they were enrolled in two consecutive semesters of EAP

writing courses taught by the participating instructors, and (b) they submitted essay drafts in the

two courses that could be analyzed for teacher feedback and student uptake.

The three teachers who taught the participating students were females between 35-52

years old. They have MA degrees in TESOL/applied linguistics and an average of 10 years of

experience teaching ESL composition. The general approach to teaching composition in the EAP

Program is genre-based and process-oriented, with teachers guiding students in examining

authentic texts in search of the underlying structure, discussing genre-related norms and

rhetorical choices, and then applying their findings to the students’ own compositions based on

current event topics discussed in class. The development of all papers involved multiple drafts

with peer and teacher feedback. Like most college-level writing courses in the U.S., the primary

attention of instructors for these courses focused on idea development and discourse structure

over grammatical accuracy.

3.2. Materials

The study examined essay drafts of two major assignments with teacher feedback

submitted by the participants enrolled in two consecutive semesters of composition – a

basic/developmental writing course (W1 hereafter) and a university-required first-year

composition course (W2 hereafter). In both of the composition courses, students wrote three



essays over the course of several weeks. The writing process included a sequence of three drafts

before the submission of the final version of each essay, and students received teacher feedback

on each draft. All submissions were made electronically via the course management system

(CMS) in use at the participating institution. The teachers downloaded the student drafts

submitted through the CMS as Microsoft Word documents, typed in their feedback using the

review function in Word to insert comments and suggested changes tracked by the software on

the drafts, resaved each individual document with their feedback, and electronically returned the

drafts with feedback to students through the CMS.

All the materials collected for this study were drawn from standard student assignments

and reflected natural teacher feedback; that is, teachers were not prompted to modify their

assignments or the type or amount of feedback they offered to students. The drafts of the first

essay analyzed in this study were written in W1; the assignment was to summarize a text and

respond persuasively to its central argument. Drafts of the second essay were collected from W2;

for that essay, the students were asked to summarize a text, analyze its rhetorical strategies, and

compose a persuasive personal response to its main claim.

The data collected for this study included: (a) two drafts, with teacher feedback, of the

first essay assignment from W1; (b) the final version of the first essay from W1; (c) one or two

drafts, with teacher feedback, of the second essay assignment from W2, as available; and (d) the

final version of the second essay from W2. Figure 1 provides a visual representation of the

writing process used in W1 and W2 and what data were collected.

[Insert Figure 1 About Here]

Table 1 provides summary information of the data collected from each class for each

student, including number of preliminary drafts, number of words in drafts, final grade for the



assignment, and the teacher for the class. For the W1 essay, drafts two and three with teacher

feedback were available from all the participating students. For the W2 essay, drafts two and

three with teacher feedback were available for two students, but only draft three was available

for the other 10 students. Since the goal of this study is simply to look at what kind of feedback

teachers provided and how students responded to that feedback, whether the feedback being

analyzed was provided on the second or third draft, or both, was not considered relevant.

[Insert Table 1 About Here]

3.3. Tools

In a pilot study, a coding sheet was developed that describes the types of written

electronic feedback offered by the teachers. Drawing on the studies of (hand)written teacher

feedback by Ferris et al. (1997), Dekhinet (2008), and Baker and Bricker (2010), TEF in this

study was classified based on the topic/focus of the comment (i.e., organization of ideas,

grammar, vocabulary, mechanics, writing process) as well as the manner in which the comment

was given (i.e., corrective or negative vs. non-corrective, direct vs. indirect, and explicit vs.

implicit). Appendix A describes in detail the coding categories used.

A second coding sheet was designed for categorizing student uptake. Uptake is

operationalized as any revisions made in response to feedback and is considered a measure of

feedback effectiveness (Lyster & Ranta, 1997; Santos, López-Serrano, & Manchón, 2010; Storch

& Wiggleswoth, 2010). Following Storch and Wigglesworth (2010), the uptake of teacher

feedback on earlier drafts of papers was coded in terms of the characteristics of the students’

responses to that feedback in later drafts: successful, unsuccessful, unattempted, or unverifiable

(see Table 2). Appendix B provides examples of how teacher feedback and student uptake were

coded.






3.4. Procedures

The two researchers and an assistant coded each instance of TEF given on the

preliminary drafts of student essays included in the study. Student revisions, if any, were then

located in the ensuing drafts and analyzed to categorize student uptake. All TEF, including

corrections (e.g., underlining, circling, highlighting, crossing out, coding, or correcting),

marginal comments, insertions, praises, etc., was coded in terms of both feedback type and

uptake results. After calibrating on a practice subset, the researchers obtained an agreement

coefficient of 89% coding the feedback in the data set. They then discussed the codes on which

they disagreed in a coding session and came to agreement on the final classification.

Any TEF consisting of multiple statements was broken down into individual ideas and

each was coded separately; the boundaries of a TEF with multiple ideas were determined based

on where the focus or characteristic of the feedback shifted (see Example 1 in Appendix B for an

example). When coding uptake, modifications students made to their drafts that were deemed as

not being in response to any TEF were not coded, even if they significantly changed the paper.

For the quantitative data analysis, the data from all students and course levels were

grouped together. Then, mean averages were calculated for each feedback and uptake

subcategory. Paired t-tests were used to determine statistically significant trends.

4. Results

This section first presents a summary of the results of the analysis of teacher e-feedback

and learner uptake. The results are then presented in sections organized according to the

categories of e-feedback and uptake that were coded. TEF and uptake of TEF are reported based

on the location and target of the TEF (content, organization, grammar, etc.), as well as on

direct/indirect and implicit/explicit distinctions.



4.1. Overview of feedback and uptake

There was no significant correlation between the length of the students’ papers and the

amount of feedback received (c = 0.08). There also was no significant correlation between the

number of teacher comments made and essay grade (A, B, or C) (c = 0.03), although this may

have been an artifact of the data set, which contained more papers with grades of A or B than

with grades of C. As shown in Table 3, although the average amount of feedback offered in W1

was higher (12.2 instances of feedback per W1 paper versus 8.1 instances per W2 paper), the

difference was not statistically significant. In keeping with the process-oriented writing approach

of the instructors, almost all of the feedback offered (96%) was “negative,” reflecting that the

intent of the teacher was to elicit a correction or modification of the text. “Negative” feedback

simply means feedback focused on error correction or suggestions for improvement, and does

not have the sense of being “bad” (Long, 1996). Only 4% of TEF consisted of praise,

encouragement, or other acknowledgements of the good qualities of the students’ drafts.

Overall, students showed successful uptake with their revisions 62.3% of the time across

both W1 and W2 combined. In W1, the students were successful in their attempts to implement

the teachers’ feedback at an impressive rate of 69.6%. The amount of successful uptake in W2,

49.3% was significantly lower than in W1 (p = .01), indicating a complex relationship between

successful uptake and course level. While one would expect that the students increase the

amount of uptake after learning how to interpret and respond to teacher feedback in W1, this was

not the case, possibly due to the increased complexity of the writing assignments and teacher

expectations. While the combined rate for unsuccessful, unattempted, and unverifiable uptake for

W2 together was significantly higher than the combined rate of these three categories for W1 (p

= .02), there were no significant differences individually in the rate of unsuccessful or



unattempted uptake between W1 and W2. The amount of unverifiable uptake – mostly in

response to teacher requests to refer to a specific course material, use the Writing Center, or keep

up the good work – did decrease significantly from W1 to W2 (p = .04), as the teachers provided

fewer such comments in writing in W2.


4.2. Analysis of teacher feedback and uptake by feedback location

The vast majority of the time (84.1%), the teachers in this study placed their feedback in

comment bubbles in the margins of the student papers using the review tool of the Microsoft

Word software. Very little feedback was provided as end- or in-text comments; in fact, only one

teacher (T2) provided in-text grammatical and lexical corrections to students in W1. Because

most feedback occurred in marginal comments, most of the uptake also occurred in response to

this category of comments. Additionally, significantly more successful uptake of marginal

comments occurred in W1 than in W2 (p = .002); the sources of this variation are discussed

below.

4.3. Analysis of feedback and uptake by feedback target

Teacher feedback was directed at a variety of targets, including content, organization,

vocabulary, grammar, mechanics, or writing process. Overall, when considering both courses

and all students, the largest percentage (42.6%) of the teachers’ comments focused on content.

Discourse organization and grammar were each the target of 15.8% of the feedback, vocabulary

and mechanics were the target of 9% and 10% (respectively), and process was the focus of less

than 2% of teacher comments. The teachers’ primary focus on content is consistent with the

process-oriented approach to composition in which content is prioritized as a higher order

concern over grammatical accuracy and mechanics, though the latter are not ignored (Ferris et



al., 2011; Keh, 1990). Interestingly, however, in this study, discourse organization and grammar

received the same amount of attention (15.8%), indicating that the teachers valued grammatical

accuracy as much as other, higher-order concerns such as discourse organization.


5.3.1. Content

Even though the amount of feedback on organization, vocabulary, grammar, and

mechanics varied as a proportion of the feedback offered in each course, the variations were not

statistically significant. Only the amount of feedback on content (including clarity, development,

overall quality, and accuracy; see Appendix A) was significantly lower in W2, dropping from

43.4% of all W1 feedback, to 40.7% of all W2 feedback (p = .04).

The proportion of successful student uptake in both courses was encouragingly high. The

only significant change from W1 to W2 was that the rate of successful uptake of feedback on all

areas of content diminished significantly from W1 to W2 (p = .01); in W1, 70.3% of teacher

feedback on content resulted in successful uptake, while in W2, 53.1% was successfully

implemented. This trend parallels the drop in teacher feedback on content from W1 to W2 noted

above, and suggests the possibility that when teachers provide less feedback on a certain aspect,

especially a complex one like content, the quality of the students’ overall response may decline.

Looking further into the subcategories of feedback on content, idea development was the

focus of most of the teachers’ comments related to content in both courses. The amount of

feedback the teachers offered in W1 and W2 about content clarity, development, and accuracy,

remained constant. Only the comments about the overall quality of the content of a student

paper, almost as frequent as comments on the development of ideas in W1, disappeared entirely

from W2 papers; the difference was statistically significant (p = .01).



Consistent with the teachers’ concentration on idea development, most of the uptake

occurred in this subcategory as well. Significant changes occurred in the amount of successful

uptake of feedback on content development, dropping from 15.6% in W1 to 11.1% in W2, and

content accuracy, dropping from 5.7% to 2.5% (although the average occurrence for uptake on

feedback focused on content accuracy was less than one instance per paper at both levels).

5.3.2. Organization

Feedback rates on aspects related to organization remained essentially unchanged across

the two courses. Paragraph order and the organization of introductions received no attention,

whereas overall quality, idea placement within body paragraphs and topic sentences received

comparatively more attention. Similarly, the rate of uptake, successful or otherwise, of feedback

on all aspects of organization was not significantly different across the two courses, with overall

successful uptake occurring on average 43.8% of the time.

5.3.3. Grammar

No changes occurred in the amount of teacher feedback focused on grammar from W1 to

W2. The feedback addressed several grammatical issues, seemingly according to student need.

Sentence structure received comparatively (but not significantly) more attention in both courses

than verb tenses, articles, subject-verb agreement, and prepositions. The amount of feedback on

the overall quality of the students’ grammar remained constant in both courses, and was higher

than the amount of feedback on the overall quality of content, organization, and vocabulary. This

indicates that these teachers value grammatical accuracy and bring it to the attention of their

students even when they refrain from commenting on the overall quality of other aspects of their

writing. It is possible that grammar may be easier to comment on as a whole, and it is also easier



for the students to study independently in order to improve their accuracy, whereas it is more

difficult to improve one’s ideas about a topic.

As shown in Table 5, with the two courses considered together, the rate of successful

uptake of the feedback on grammar (see Appendix A for sub-categories) was a high 75%. In W1,

95% of grammar-focused feedback resulted in successful uptake, but this rate dropped

significantly (p = .03) in W2 to 41.7%, while the proportion of unsuccessful attempts rose in W2

from W1. Additionally, the students seemed willing to take on all of the feedback on grammar,

whether successfully or unsuccessfully. There was no unattempted or unverifiable uptake of

feedback on grammar in either course.


The highest amount of successful student uptake occurred in the subcategory of feedback

on sentence structure, and it followed the patterns noted above about other uptake subcategories,

in that it decreased in W2 compared to W1, though not significantly. This was paralleled by an

increase in unsuccessful attempts to implement feedback on sentence structure. Most of the

feedback on verbs and articles was also implemented successfully in both courses, and more so

in W1 than in W2, without being accompanied by an increase in the rate of unsuccessful or

ignored feedback.

5.3.4. Vocabulary, mechanics, and process

As shown in Table 4, the rate of teacher feedback on vocabulary and mechanics each

averaged only about one comment per paper across both courses, reflecting the teachers’ primary

focus instead on the writers’ development of content and organization, which together averaged

about five comments per paper. When teachers did provide comments on vocabulary, the

feedback typically focused on word choice and phrasing; the main focus of feedback on



mechanics dealt primarily with documentation of sources followed by comments on punctuation

and formatting. Teacher feedback on the writing process was fairly rare, averaging just one

comment per every five papers evaluated. Uptake patterns were similar to the ones discussed

above, with most of the feedback being implemented successfully; due to the low incidence of

feedback on vocabulary, mechanics, and process, uptake in these areas was not analyzed in

further detail.

4.4. Analysis of direct feedback, indirect feedback, and uptake of direct and indirect feedback

In both courses and for both groups of students, all of the participating teachers provided

overwhelmingly direct feedback (74.3%), consisting of directives or instructions to execute a

certain change (mostly at content-level), praise and statements of agreement with content or

correct use forms, corrections of incorrect interpretations or forms, and statements that

something was wrong and explanations of rules accompanied by examples of correct usage. The

use of direct and indirect feedback was not significantly different between W1 and W2.

In W1, the subcategory of direct feedback most frequently used consisted of directives or

requests to change something in the draft (26.8%). Another 23% of the direct feedback consisted

of rules and explanations about how a revision should be done, without the revision or an

example being provided. An additional 23% of the direct feedback simply stated that something

was wrong or incorrect in the text. Finally, 18% of the direct feedback consisted of explicit

corrections while 9.4% consisted of statements that praised an aspect of the paper or expressed

agreement with a train of thought expressed in it.

In W2, more of the direct feedback (51.7%) included rule explanations; 20% of the direct

feedback included statements indicating that something in the text was wrong, and directives

continued to be present, but significantly less than in W1 (16.8%; p = .04). The amount of direct



corrections decreased in W2, but the significance of this change is doubtful as it was clearly a

teacher effect; T2 used in-text corrections of grammar and lexical choice much more than the

other two participating teachers. The amount of praise or agreement was less frequent in W2 as

well, though not significantly so (3.4%).

As shown in Table 6, successful uptake of direct feedback was significantly higher in W1

than in W2 (p = .01). In W1, 66.3% of the direct feedback resulted in successful uptake, while in

W2, only 46.2% did. Although not significant differences, the decrease in successful uptake from

W1 to W2 coincided both with an increase from W1 to W2 in unsuccessful uptake, from 12% to

38.5%, as well as an increase in unattempted uptake, from 10.9% to 12.3%. The amount of

unverifiable uptake on direct feedback (including comments like, “Go to the Writing Center” and

“Great!”) dropped significantly from W1 (10.8%) to W2 (3.1%). The occurrence of indirect

feedback was infrequent compared to that of direct feedback, and there were no significant shifts

in its use or in student uptake when comparing W1 to W2.


4.5. Analysis of implicit feedback, explicit feedback, and uptake of implicit and explicit

feedback

As with direct feedback, the vast majority of feedback provided by all the teachers across

both courses was explicit feedback (79%). Explicit feedback was given through corrections of

forms or content, directives (requests) to execute a change, the use of codes and other

explanations to indicate what aspect of a form was incorrect, and statements that something was

wrong in the text. Overall, most of the explicit feedback (59.5%) was implemented successfully

by the students, while 25.3% resulted in unsuccessful uptake and 10.1% was not addressed by

students in the ensuing draft. As with direct feedback, significantly more explicit feedback



resulted in successful uptake in W1 than in W2 (p = .05). The focus of explicit feedback, as well

as the resulting uptake rates, aligned closely with the results discussed above with regard to

direct feedback, suggesting that the distinction between direct and explicit feedback is not

particularly useful in discussions of written feedback.

5. Conclusions and discussion

In sum, the current study found the following with regard to teacher e-feedback (TEF):

the amount of TEF did not depend on the length of the students’ papers;

TEF was almost always placed in marginal comment bubbles in Microsoft Word

(84.1%);

TEF was predominantly corrective/negative (96%);

the largest percentage (42.6%) of TEF focused on content, with organization

(especially idea development) and grammar being the next most important areas

of focus (about 15% each);

significantly more content-focused TEF occurred in W1;

TEF was overwhelmingly direct (including directives/requests for changes, rule

explanations, and corrections) (74.3%);

TEF in W1 was significantly more often given as a directive.

With regard to student uptake of TEF, the current study found the following:

the overall rate of successful uptake was high (62.3%), with the highest rate being

in response to TEF focused on grammar (75%);

significantly more successful uptake occurred in W1, especially following direct

TEF and TEF on content;



no significant difference emerged between explicit and direct TEF and their

uptake.

Notably, the TEF analyzed here shares many of the characteristics of handwritten

feedback described in previous studies: (1) Ferris et al. (1997) found that most written feedback

given by teachers consisted of marginal comments; similarly, most of the TEF analyzed in this

study was placed in marginal comment bubbles in Microsoft Word. (2) Ferris et al. (1997; see

also Connors & Lunsford, 1993; Sommers, 1982) found that most written teacher feedback was

directive, often taking the form of statements and imperatives, and sometimes consisting of

requests for information or revisions, findings that parallel the results in this study. (3) In this

study, TEF was primarily content and meaning-oriented, which is in keeping with the results in

Ferris et al. (1997, 2011) and, in CALL, Samburskiy and Quah (2014) and Ware and O’Dowd

(2008) (cf. Montgomery & Baker, 2007). (4) In keeping with current SLW scholarship (e.g.,

Beason, 2004; Evans et al., 2010; Ferris, 2006, 2011; Hinkel, 2004), higher-order concerns (Keh,

1990) focused the teachers’ response in this study, though lower-order concerns were not

neglected. (5) The present study confirms previous observations that students tend to make

revisions where they receive feedback (electronic or written) (Ferris, 2006; Martin-Beltran &

Chen, 2013; Tuzi, 2005), as TEF successfully elicited appropriate revisions on a variety of

aspects of the student essays, although somewhat surprisingly the overall amount of successful

uptake in W1 was significantly higher than in W2. (6) Direct, explicit e-feedback, which is

preferred by both teachers and students, is effective whether it is handwritten or electronic, as it

results in more successful student uptake than indirect, implicit e-feedback (Baker and Bricker,

2010; Bitchener, 2008; Bitchener & Knoch, 2008 a and b; Ellis, N., 1993; Ellis, Loewen, &

Erlam, 2006; Ellis et al., 2008; Ellis, 2009; Sheen, 2007).



The study has pedagogical and theoretical implications regarding SLW and SLA. It

confirms the value of not only direct but also specific feedback, be it electronic or handwritten.

The teachers in this study provided very little general e-feedback about the overall quality of the

students’ papers and few generalized end comments. The results validate for e-feedback the

findings on handwritten feedback of Ferris et al. (1997), who found that students tend to make

the most substantial revisions in response to text-specific teacher comments rather than general

or positive (i.e., praising) comments. Some CALL studies also have shown that e-feedback leads

to uptake (Schultz, 2000; Tuzi, 2005). Some have shown that specific metalinguistic feedback

(the equivalent of rule explanations in the current study) is particularly effective (Heift, 2004;

Sauro, 2009), especially with less proficient language learners (Heift, 2010). This suggests that

teachers, tutors, and even peers should be trained to use specific feedback.

The distribution and characteristics of teacher feedback and student uptake offer a

window into the relative difficulty and complexity of various aspects of the writing process, as

well as the SLA process. The students’ general success with uptake shows that, for the most part,

the feedback was noticed (Schmidt, 1990). The students’ attempts to implement the teacher

feedback also indicates the presence of pushed output (Swain, 1985, 1995). However, the fact

that the amount of successful uptake decreased in W2 suggests that, as the writing tasks became

more complex, students found it more challenging to implement teacher feedback, which tended

to focus on rhetorical, higher-order issues rather than simply lexico-grammatical, lower-order

issues. Because most of the feedback and uptake were related to essay content, it seems that

content remains the most challenging for the students across proficiency levels, or at least that

the teachers in this study perceived it to be so.



This study further confirms that teachers can be reassured of the usefulness of the

feedback they provide on SLW assignments, but they should expect uptake to fluctuate as

content and tasks becomes more complex. In fact, teachers can expect the nature of their own

feedback to change as the writing tasks change. Like Ferris et al. (1997) and studies quoted

therein, this study found that the amount of teacher feedback decreased as student proficiency

level increased (in this case, from W1 to W2). Tuzi (2005) found a similar pattern in peer e-

feedback. This trend is not unexpected as less advanced writers and drafts likely need more

feedback. In our study, an interesting fact is that the largest drop in TEF from W1 to W2 also

occurred in the category of idea development and content. The reason may be that as students’

proficiency levels and writing abilities improve, they are better able to understand and respond,

so need less feedback on basic ideas and content in their drafts. In addition, it appears that the

TEF that is given on content in more advanced stages of writing is also more complex, making it

harder for students to implement the feedback, as suggested by the fact that there was less

successful uptake of TEF about content in W2.

A limitation of this study is the relatively small number of participating students and

teachers, which limits the broader generalizability of the results. As a first attempt to describe the

previously unexplored characteristics of TEF, this study took a predominantly quantitative

approach and isolated TEF from other kinds of feedback the students might have received in

class, peer reviews, teacher conferences, or the writing center. Aside from a replication with a

higher number of participants, it would be useful to conduct an exploration into how TEF

complements other sources of feedback and over a longer period of time. In addition, exploring

student and teacher perspectives of e-feedback would help clarify some of the decisions made

with regard to offering and responding to feedback. More than anything, the field of SLW would



benefit from more studies of TEF. So far, the merits of peer and tutor e-feedback have been

studied more than TEF, even though teachers likely provide feedback more frequently and

effectively, and are expected to do so by students ((Ferris et al., 1997; Guénette, 2007;

Hedgecock & Lefkowitz, 1994; Hyland & Hyland, 2001; Leki, 1990). The research developing

at the intersection of SLW and CALL should develop a thorough understanding of TEF as a

whole before narrowing down its focus to specific feedback strategies, in order to maximize its

pedagogical relevance. A typology of TEF should also further clarify the role of praise, possibly

in relation to the learners’ first language and culture. Although Hyland and Hyland (2001)

observed that students find positive remarks motivating even when they understand that it often

is a mere preamble to criticism, Baker and Bricker (2010) have hypothesized that teachers may

refrain from giving praise because students often fail to interpret positive and indirect feedback

as corrective. Why teachers offer little praise of student writing and whether more of it would

result in more uptake remain questions for future research.



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http://www.gse.uci.edu/person/warschauer_m/docs/feedback.pdf

Appendix A

Teacher Feedback: Coding Categories and Brief Examples

1. Target of Teacher Feedback

General

Q = Overall quality of essay in all its aspects. Ex: "Excellent" or "This paper/paragraph

needs much work in several areas." on an entire paragraph or larger part of a paper.

Discourse level

C = Content

Cc = Clarity or understandability. Ex: “What do you mean here?” “This is not

clear.” “Clarify.”

Cd = Development or lack of development. Ex: “These are the same ideas as in

the summary.” “You are repeating points made earlier.”

Cq = Overall quality of content. Ex: "Excellent ideas!" about a whole paragraph

or essay.

Ca = Accuracy of information, truth value of a claim, accuracy of interpretation

Ex: "This is a misinterpretation of the text." "The author does not say that." "You

misunderstood the idea."

O = Organization, coherence, cohesion

Otr = Transitions. Ex: “You need transitions between the ideas in this paragraph.”

Oth = Thesis statement. Ex: “Excellent thesis statement!” “I can’t find your

thesis.”

Oto = Topic sentence. Ex: “Is this your topic sentence?”



Oq = Overall quality of organization. Ex: “Your paper is (not) well organized.”

Och = Coherence, cohesion. Ex: “Connect these ideas to convince the reader.”

Op = Idea placement. Ex: “This belongs at the end of the paragraph.”

Oo = Paragraph order. Ex: “The rhetorical analysis paragraph is missing/should

be first.”

Form level

V = Vocabulary

Vw = Word choice, collocations, phrasing. Ex: “This is not the right word for

what I think you’re trying to say. Look it up.” “The author shows researches

evidence…”

Vq = Overall quality of vocabulary “In your revision, please pay attention to word

choice.”

G = Grammar/Syntax and morphology

Gs = Sentence structure

Go = Ommission (e.g., subject)

Gw = Word order

Gv = Verb tense or form

Gn = Noun form

Gart = Article

Gagr = Agreement (e.g., s-v, pronoun)

Gp = Prepositions

Gpron = Pronoun

Gq = Overall quality of grammar



M = Mechanics

Mp = Punctuation

Ms = Spelling

Md = Documentation or attribution

Mf = Formatting and style

Mq = Overall quality of mechanics

P = Writing process

Pr = Revision. Ex: “You need to revise this paragraph carefully.”

Pw = Writing Center assistance. Ex: “I encourage you to make an appointment

with the Writing Center.”

Wq = Overall quality of revisions. Ex: “This draft is (not) much improved.”

2. Directness/Indirectness of corrective feedback (related to how the target form is provided)

Direct feedback

Dc = Correction (correct form provided; replacement, reformulation, insertion)

Ds = Explicit statement that something is wrong or problematic. Ex: “This

explanation does not work.” “The word should not be capitalized.”

Dr = Rule or explanation is provided. Ex: “In English, each sentence must have a

subject.” (Rule); “This is a fragment because the sentence doesn't have a verb.”

(Explanation); “The author made several important claims, and all of those claims

should be included in the summary.” (Explanation)

Dd = Directive. Ex: “Use the SVO word order here.” “You have to use quotation

marks around this phrase.” “Avoid the passive voice.”



De = Example is provided. Ex: “This is not the only consequence of the conflict.

For example, they are not allowed to pray there, either.”

Du = Incorrect form is crossed out.

Da = Acknowledgement of correct language usage; agreement with content.

“Yes! Well said!”

Indirect feedback

Ig = Error is graphically marked or enhanced: underlining, highlighting, circling

It = Error count is provided

Ict = Error codes are used (wc for word choice, wo for word order, etc.)

3. Implicitness/Explicitness of corrective feedback (related to how the learner is being let know

that his/her usage differs from the target)

Explicit feedback

Ec = Correction or evaluative comment

Ed = Directive (“Do it” type of statements. May also offer the specific structure to

use. Ex: “Use either…or.”)

Ect = Error codes

Ep = Explanations/statements that something is wrong.

Ew = Examples.

Implicit feedback

Icc = Confirmation check. Ex: “Do you mean they were persecuted?”

Icr = Clarification request. Ex: “What do you mean here?”

Ip = Explanation without correction. Ex: “I would like to see more variety in the

way each paragraph begins.”



Iw = Indicates something is wrong but does not provide a correction. Ex: “No, not

‘also’.”/”You haven't quoted this correctly.”

4. Feedback Charge

Rs = Praise; encouragement; acknowledgement of something positive.

Rn = All feedback that is not Rs.



Appendix B

Expanded Examples of Feedback, Uptake, and Coding

Example 1.

Student text in Draft 2:

There are some ideas from different delegates about “distracted driving” were mentioned by

Joseph B. White in the “Driving While Texting: Is It the New DWI?”

Student text with teacher’s electronic feedback:

Student revision in Draft 3 and final submission:

Some public issues about “distracted driving” were mentioned by Joseph B. White in the

“Driving While Texting: Is It the New DWI?”

Code for teacher feedback:

Part 1: State your topic by starting with the subject of the sentence, not a neutral expression like

this. Code: Vw Dd Ep Rn

Part 2: “There is/are” makes for a weak beginning. Code: Vw Ds Ew Rn

Code for revision/uptake:

successful (S)

Example 2:


According to the article, the reason they did that is because mercy hospital sees at least four

Hmong people and their belief caused a conflict with doctors belief. Therefore[teacher comment



javascript:parent.onLocalLink('_msocom_1',window.frameElement)

2] , mercy hospital has a training program that teaching Hmong people about the western-style

medicine.


Student revision in Draft 3:

According to the article, the reason they did that is because Mercy Hospital sees at least four

Hmong people daily, and their beliefs have caused conflicts with the doctors’ beliefs. Therefore,

Mercy Hospital has a training program to teach Hmong people about the western-style

medicine.


Cd Ds Ew Rn


Unsuccessful (U)

Example 3:


The first reason that the international community doesn’t cooperate because it is a Muslim

community and usually the religious hard to convinced to change their religion; as a result, only

Muslim country such as Saudi Arabia offer a big amount of money to help Pakistanis recover

from their catastrophe.




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Student revision in Draft 3:

The international community doesn’t know how bad the situation is in the Pakistan since the

media doesn’t show the situation clearly. Moreover, the author doesn’t include any emotional

images to his article since he is an encomiast. If the world could see the pictures that show

people who are fighting to get some food, a picture of big crowd of people including a lot of

children, all religions such as Muslims, Christian, and Catholic etc, would move quickly to help

the people there because of humanity.


Ca Ds Ep Rn


Successful



Documents

Learner Uptake of Teacher Electronic Feedback in ESL